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imagery with albedo-based and kernel-based approaches

by Robert S. Rand, Ronald G. Resmini, David W. Allen
"... intimate mixtures of materials in hyperspectral ..."
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intimate mixtures of materials in hyperspectral

A kernel-based approach to direct action perception

by O. Kroemer, E. Ugur, E. Oztop, J. Peters - In IEEE International Conference on Robotics and Automation , 2012
"... Abstract—The direct perception of actions allows a robot to predict the afforded actions of observed objects. In this paper, we present a non-parametric approach to representing the affordance-bearing subparts of objects. This representation forms the basis of a kernel function for computing the sim ..."
Abstract - Cited by 12 (2 self) - Add to MetaCart
Abstract—The direct perception of actions allows a robot to predict the afforded actions of observed objects. In this paper, we present a non-parametric approach to representing the affordance-bearing subparts of objects. This representation forms the basis of a kernel function for computing

A Kernel-based Approach to Document Retrieval

by Albert Gordo, Jaume Gibert, Ernest Valveny, Marçal Rusiñol
"... In this paper we tackle the problem of document image retrieval by combining a similarity measure between documents and the prob-ability that a given document belongs to a certain class. The mem-bership probability to a specific class is computed using Support Vector Machines in conjunction with sim ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
with similarity measure based ker-nel applied to structural document representations. In the presented experiments, we use different document representations, both vi-sual and structural, and we apply them to a database of historical documents. We show how our method based on similarity kernels outperforms

A new kernel-based approach for system identification

by Giuseppe de Nicolao, Gianluigi Pillonetto , 2008
"... ..."
Abstract - Cited by 4 (3 self) - Add to MetaCart
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A Relational Kernel-based Approach to Scene Classification

by Laura Antanas, Paolo Frasconi, Mcelory Hoffmann, Tinne Tuytelaars, Luc De Raedt
"... Real-world scenes involve many objects that interact with each other in complex semantic patterns. For example, a bar scene can be naturally described as having a variable number of chairs of similar size, close to each other and aligned horizontally. This high-level interpretation of a scene relies ..."
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, today recent successes in combining them with statistical learning principles motivates us to reinvestigate their use. In this paper we show that relational techniques can also improve scene classification. More specifically, we employ a new relational language for learning with kernels, called k

A new kernel-based approach for linear . . .

by Gianluigi Pillonetto , et al. - AUTOMATICA 46 (2010) 81–93 , 2010
"... ..."
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A Kernel Based Approach to Maximum Entropy Mappings

by unknown authors
"... Abstract- We discuss a kernel based method for learning maximum entropy mappings from exemplars. Information theoretic signal processing has been ex-amined by many authors. The method presented here is related to the approaches of Linsker [l, 21, Bell and Sejnowski [3], and Viola et a1 [4]. In this ..."
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Abstract- We discuss a kernel based method for learning maximum entropy mappings from exemplars. Information theoretic signal processing has been ex-amined by many authors. The method presented here is related to the approaches of Linsker [l, 21, Bell and Sejnowski [3], and Viola et a1 [4

Y: A single kernel-based approach to extract drug-drug interactions from biomedical literature

by Yijia Zhang, Hongfei Lin, Zhihao Yang, Jian Wang, Yanpeng Li - PLOS ONE
"... When one drug influences the level or activity of another drug this is known as a drug-drug interaction (DDI). Knowledge of such interactions is crucial for patient safety. However, the volume and content of published biomedical literature on drug interactions is expanding rapidly, making it increas ..."
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it increasingly difficult for DDIs database curators to detect and collate DDIs information manually. In this paper, we propose a single kernel-based approach to extract DDIs from biomedical literature. This novel kernel-based approach can effectively make full use of syntactic structural information

Outlier robust system identification: a Bayesian kernel-based approach

by Giulio Bottegal Aleks, R Y. Aravkin, Gianluigi Pillonetto
"... Abstract: In this paper, we propose an outlier-robust regularized kernel-based method for linear system identification. The unknown impulse response is modeled as a zero-mean Gaussian process whose covariance (kernel) is given by the recently proposed stable spline kernel, which encodes information ..."
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Abstract: In this paper, we propose an outlier-robust regularized kernel-based method for linear system identification. The unknown impulse response is modeled as a zero-mean Gaussian process whose covariance (kernel) is given by the recently proposed stable spline kernel, which encodes information

A kernel-based approach to learning semantic parsers. Doctoral Dissertation Proposal

by Rohit J. Kate , 2005
"... Semantic parsing involves deep semantic analysis that maps natural language sentences to their formal executable meaning representations. This is a challenging problem and is critical for developing user-friendly natural language interfaces to computing systems. Most of the research in natural langu ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
to filling a single semantic frame. In this proposal, we present a new approach to semantic parsing based on string-kernel-based classification. Our system takes natural language sentences paired with their formal meaning representations as training data. For every production in the formal language grammar
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